Abstract
Understanding the genetic basis of fitness-related trait variation has long been of great interest to evolutionary biologists. Secondary sexual characteristics, such as horns in bovids, are particularly intriguing since they can be potentially affected by both natural and sexual selection. Until recently, however, the study of fitness-related quantitative trait variation in wild species has been hampered by a lack of genomic resources, pedigree, and/or phenotype data. Recent innovations in genomic technologies have enabled wildlife researchers to perform marker-based relatedness estimation and acquire adequate loci density, enabling both the “top-down” approach of quantitative genetics and the “bottom-up” approach of association studies to describe the genetic basis of fitness-related traits. Here we combine a cross species application of the OvineHD BeadChip and horn measurements (horn length, base circumference, and volume) from harvested thinhorn sheep to examine the heritability and to perform a genome-wide single-nucleotide polymorphism association study of horn size in the species. Thinhorn sheep are mountain ungulates that reside in the mountainous regions of northwestern North America. Thinhorn sheep males grow massive horns that determine the social rank and mating success. We found horn length, base circumference, and volume to be moderately heritable and two loci to be suggestively associated with horn length.
Highlights
The genetic basis of trait diversity is a fundamental area of inquiry in evolutionary biology
We investigated the genetic basis of fitness-related traits in Dall’s sheep by genotyping 192 animals using a cross-species application of a domestic sheep high-density single-nucleotide polymorphisms (SNPs) array (>600,000 loci)
We achieve a typical conversion rate of about 1% (Miller et al, 2012; Sim et al, 2016), which resulted in an SNP panel of ~6,000 loci, comparable to that of a medium-density SNP array
Summary
The genetic basis of trait diversity is a fundamental area of inquiry in evolutionary biology. Recent advances in genomic technologies have ushered in a new age of inquiry into the genetic basis of traits by dramatically lowering the per-unit cost of obtaining genetic data, for nonmodel organisms (Davey et al, 2011; Helyar et al, 2011). This drop in price and ease of genetic data collection have advanced our ability to feasibly investigate a large-enough number of loci to reasonably interrogate the genome for associations with phenotype (Garvin et al, 2010)
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